Falling Prediction and Recovery Control for a Humanoid Robot

Tianqi Yang; Weimin Zhang; Zhangguo Yu; Libo Meng; Chenglong Fu; Qiang Huang

doi:10.1109/HUMANOIDS.2018.8625000

Falling Prediction and Recovery Control for a Humanoid Robot

Tianqi Yang, Weimin Zhang^*, Zhangguo Yu, Libo Meng, Chenglong Fu, Qiang Huang

^*Corresponding author for this work

School of Mechatronical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

It is very easy for biped robots to fall down. Some previous studies have been carried out to detect the fall state and protect the robot from damage. But it is not enough to detect a fall. It is very important for the biped robot to predict whether it will fall in the future based on the current state. In this paper, we consider a fall state predicted problem for bipedal robots. Based on the D 'Alembert principle, this method can predict the fall state at the moment the biped robot deviates from the normal state in every conditions such as standing and walking. It can give the robot more time to recover from the unstable state or protect itself from damage. And its stable control strategy matching the proposed method is also proposed to protect the robot from falling. The result is verified via simulations.

Original language	English
Title of host publication	2018 IEEE-RAS 18th International Conference on Humanoid Robots, Humanoids 2018
Publisher	IEEE Computer Society
Pages	1073-1079
Number of pages	7
ISBN (Electronic)	9781538672839
DOIs	https://doi.org/10.1109/HUMANOIDS.2018.8625000
Publication status	Published - 2 Jul 2018
Event	18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018 - Beijing, China Duration: 6 Nov 2018 → 9 Nov 2018

Publication series

Name	IEEE-RAS International Conference on Humanoid Robots
Volume	2018-November
ISSN (Print)	2164-0572
ISSN (Electronic)	2164-0580

Conference

Conference	18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018
Country/Territory	China
City	Beijing
Period	6/11/18 → 9/11/18

Access to Document

10.1109/HUMANOIDS.2018.8625000

Cite this

Yang, T., Zhang, W., Yu, Z., Meng, L., Fu, C., & Huang, Q. (2018). Falling Prediction and Recovery Control for a Humanoid Robot. In 2018 IEEE-RAS 18th International Conference on Humanoid Robots, Humanoids 2018 (pp. 1073-1079). Article 8625000 (IEEE-RAS International Conference on Humanoid Robots; Vol. 2018-November). IEEE Computer Society. https://doi.org/10.1109/HUMANOIDS.2018.8625000

@inproceedings{a0af5962c82748388b56352f44b252fd,

title = "Falling Prediction and Recovery Control for a Humanoid Robot",

abstract = "It is very easy for biped robots to fall down. Some previous studies have been carried out to detect the fall state and protect the robot from damage. But it is not enough to detect a fall. It is very important for the biped robot to predict whether it will fall in the future based on the current state. In this paper, we consider a fall state predicted problem for bipedal robots. Based on the D 'Alembert principle, this method can predict the fall state at the moment the biped robot deviates from the normal state in every conditions such as standing and walking. It can give the robot more time to recover from the unstable state or protect itself from damage. And its stable control strategy matching the proposed method is also proposed to protect the robot from falling. The result is verified via simulations.",

author = "Tianqi Yang and Weimin Zhang and Zhangguo Yu and Libo Meng and Chenglong Fu and Qiang Huang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018 ; Conference date: 06-11-2018 Through 09-11-2018",

year = "2018",

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doi = "10.1109/HUMANOIDS.2018.8625000",

language = "English",

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Yang, T, Zhang, W , Yu, Z, Meng, L, Fu, C & Huang, Q 2018, Falling Prediction and Recovery Control for a Humanoid Robot. in 2018 IEEE-RAS 18th International Conference on Humanoid Robots, Humanoids 2018., 8625000, IEEE-RAS International Conference on Humanoid Robots, vol. 2018-November, IEEE Computer Society, pp. 1073-1079, 18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018, Beijing, China, 6/11/18. https://doi.org/10.1109/HUMANOIDS.2018.8625000

Falling Prediction and Recovery Control for a Humanoid Robot. / Yang, Tianqi; Zhang, Weimin ; Yu, Zhangguo et al.
2018 IEEE-RAS 18th International Conference on Humanoid Robots, Humanoids 2018. IEEE Computer Society, 2018. p. 1073-1079 8625000 (IEEE-RAS International Conference on Humanoid Robots; Vol. 2018-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Yang, Tianqi

AU - Zhang, Weimin

AU - Yu, Zhangguo

AU - Meng, Libo

AU - Fu, Chenglong

AU - Huang, Qiang

PY - 2018/7/2

Y1 - 2018/7/2

N2 - It is very easy for biped robots to fall down. Some previous studies have been carried out to detect the fall state and protect the robot from damage. But it is not enough to detect a fall. It is very important for the biped robot to predict whether it will fall in the future based on the current state. In this paper, we consider a fall state predicted problem for bipedal robots. Based on the D 'Alembert principle, this method can predict the fall state at the moment the biped robot deviates from the normal state in every conditions such as standing and walking. It can give the robot more time to recover from the unstable state or protect itself from damage. And its stable control strategy matching the proposed method is also proposed to protect the robot from falling. The result is verified via simulations.

AB - It is very easy for biped robots to fall down. Some previous studies have been carried out to detect the fall state and protect the robot from damage. But it is not enough to detect a fall. It is very important for the biped robot to predict whether it will fall in the future based on the current state. In this paper, we consider a fall state predicted problem for bipedal robots. Based on the D 'Alembert principle, this method can predict the fall state at the moment the biped robot deviates from the normal state in every conditions such as standing and walking. It can give the robot more time to recover from the unstable state or protect itself from damage. And its stable control strategy matching the proposed method is also proposed to protect the robot from falling. The result is verified via simulations.

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Falling Prediction and Recovery Control for a Humanoid Robot

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